Data Engineer — PySpark + AWS Glue

Yadimen Consulting · Python · Java · SQL · ETL/ELT · AWS Glue · 4 months ago

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Salary

≈ $15k – $38k per year (Estimated)

Location

In office (Bengaluru)

Seniority

Middle · 4+ years exp

Employment

Full-Time

Confirmed on the employer's own hiring board on Oct 30, 2026. First seen by Alion on Jun 1, 2026. Yadimen Consulting scores B on the Alion truth index.

Overview

Company

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Profile match

Yadimen Consulting

Headquartered in London, United Kingdom, Yadimen Consulting is a specialized management and technology consulting practice focused on financial services transformation across Europe, the Middle East, and Africa (EMEA). The firm provides expert strategic advisory, program delivery, and specialized engineering services across critical areas such as regulatory compliance, operational resilience, core platform modernization, payments, lending, and digital customer experience. By combining senior industry practitioners with an AI-augmented intelligence layer, the company helps banks, financial institutions, and global enterprises navigate complex regulatory frameworks, upgrade legacy IT infrastructure, and accelerate secure digital transformation.

yadimen.com · HQ: London, United Kingdom · 1001-5000 employees · Est. 2017

Tech stack of Yadimen Consulting

Data Engineer - PySpark + AWS Glue ETL & Data Pipelines | 2 Openings Location: Remote (UK)

Employment Type: Contract / Permanent Experience Level: 4-8 Years Openings: 2

About the Role We are looking for a skilled Data Engineer with solid hands-on experience in PySpark, AWS Glue, and ETL development to build and maintain scalable, production-grade data pipelines on AWS. You will be part of a delivery-focused team working on complex data engineering challenges, contributing to data lake architecture and end-to-end pipeline development.

Requirements

Key

Responsibilities

Design, develop, and maintain scalable ETL pipelines using PySpark and AWS Glue
Build and optimise data ingestion, transformation, and loading workflows
Orchestrate data workflows using AWS Step Functions
Develop serverless functions using AWS Lambda (Python)
Work with data lake architectures on AWS to support analytical use cases
Ensure pipeline reliability, monitoring, and performance optimisation Required Skills & Experience
Strong hands-on experience with PySpark and AWS Glue
Proven track record in ETL pipeline development and optimisation
Experience orchestrating workflows with AWS Step Functions
Proficiency in serverless development using AWS Lambda (Python)
Good SQL skills and a solid understanding of data processing principles Nice to Have
Exposure to Java-based microservices
Understanding of REST APIs and backend service integrations

• Experience working with AWS-based data lakes

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